WEBVTT FILE 1 00:00:00.050 --> 00:00:04.090 [data sounds] 2 00:00:04.110 --> 00:00:08.150 The GPM mission is a sophisticated 3 00:00:08.170 --> 00:00:12.190 network of satellites, covering the entire globe in less than three hours, 4 00:00:12.210 --> 00:00:16.230 giving us an unprecedented picture of precipitation, 5 00:00:16.250 --> 00:00:20.270 from rain to falling snow, hurricanes to monsoons, 6 00:00:20.290 --> 00:00:24.310 droughts and floods. So how do we get all of that information 7 00:00:24.330 --> 00:00:28.340 out of this? The short answer: Tons of data 8 00:00:28.360 --> 00:00:32.350 from all over. 9 00:00:32.370 --> 00:00:36.360 As GPM takes snapshots at precipitation, 10 00:00:36.380 --> 00:00:40.400 like in a major storm, the data gathered is transmitted 11 00:00:40.420 --> 00:00:44.420 to a network of satellites called TDRSS. 12 00:00:44.440 --> 00:00:48.440 Erich Stocker: The important thing to recognize is that the GPM satellite does not 13 00:00:48.460 --> 00:00:52.470 talk directly to the Earth; it talks to the communications satellite 14 00:00:52.490 --> 00:00:56.520 which is known as TDRSS. And the TDRSS satellites 15 00:00:56.540 --> 00:01:00.550 talk to a ground station, which is at White Sands, New Mexico, 16 00:01:00.570 --> 00:01:04.570 and that's a very effective way to get 17 00:01:04.590 --> 00:01:08.580 continuous data, which cannot be gotten otherwise, unless you do 18 00:01:08.600 --> 00:01:12.680 direct broadcast and have many, many ground stations, which isn't 19 00:01:12.700 --> 00:01:16.740 as effective as going through the TDRSS system. 20 00:01:16.760 --> 00:01:20.890 The White Sands Ground Station then sends information about the health and 21 00:01:20.910 --> 00:01:24.940 geolocation of the GPM Core satellite to the hub of all 22 00:01:24.960 --> 00:01:29.020 of this activity, the Missions Operations Center, located at NASA's 23 00:01:29.040 --> 00:01:33.080 Goddard Space Flight Center. The raw data streams 24 00:01:33.100 --> 00:01:37.190 into Goddard's Precipitation Processing System, or PPS. 25 00:01:37.210 --> 00:01:41.220 The data from the radar is routed through GPM's partner, 26 00:01:41.240 --> 00:01:45.250 the Japan Aerospace Exploration Agency, for initial processing 27 00:01:45.270 --> 00:01:49.270 and then is sent back to the PPS. George Huffman: The data that come down from 28 00:01:49.290 --> 00:01:53.410 the satellite are actually not precipitation. They're in the form of radiances, 29 00:01:53.430 --> 00:01:57.510 in the case of the microwave instruments, or reflectivities, in the case 30 00:01:57.530 --> 00:02:01.650 of the radar. The computer codes I've been talking about--the algorithms-- 31 00:02:01.670 --> 00:02:05.700 are the way we get from numbers 32 00:02:05.720 --> 00:02:09.750 that nobody including me can directly interpret to the thing we care about, 33 00:02:09.770 --> 00:02:13.790 which is precipitation. The GPM mission is not just the Core 34 00:02:13.810 --> 00:02:17.840 spacecraft, but also a constellation of existing satellites 35 00:02:17.860 --> 00:02:21.890 from partners around the world. Each constellation member may have its own 36 00:02:21.910 --> 00:02:25.910 unique scientific objectives, but they all contribute data to the PPS 37 00:02:25.930 --> 00:02:29.940 in order to develop global precipitation products. 38 00:02:29.960 --> 00:02:33.950 Erich Stocker: The Precipitation Processing System gets data from the satellite and 39 00:02:33.970 --> 00:02:38.000 various other sources and creates the science products 40 00:02:38.020 --> 00:02:42.050 that are going to be used for both applications purposes, that is 41 00:02:42.070 --> 00:02:46.060 societal benefits, and scientific research. The PPS then produces 42 00:02:46.080 --> 00:02:50.110 a suite of data products, including both instrument specific and 43 00:02:50.130 --> 00:02:54.150 merged data, unifying the data gathered by the international 44 00:02:54.170 --> 00:02:58.170 partner satellites that make up the GPM constellation. 45 00:02:58.190 --> 00:03:02.210 George Huffman: You could compare this to making soup. We have 46 00:03:02.230 --> 00:03:06.240 carrots, and we have onions, and we have potatoes. 47 00:03:06.260 --> 00:03:10.250 They're all vegetables. And so you have to wash them, peel them, 48 00:03:10.270 --> 00:03:14.300 take out the bad spots. That's a really important step, you don't want your soup to 49 00:03:14.320 --> 00:03:18.360 taste bad. When you get done, of course, you have to taste test it to make sure the 50 00:03:18.380 --> 00:03:22.410 seasoning right, and then you have to serve it. And so each of those steps 51 00:03:22.430 --> 00:03:26.460 in a mathematical sense, is what we have to do in order to take all the 52 00:03:26.480 --> 00:03:30.490 diverse sources of information and end up with a unified product 53 00:03:30.510 --> 00:03:34.550 which the user finds to be useful. These precipitation 54 00:03:34.570 --> 00:03:38.580 products will be useful in many societal applications, like 55 00:03:38.600 --> 00:03:42.610 hydrologic modeling, mapping potential natural disasters, 56 00:03:42.630 --> 00:03:46.630 agricultural modeling, weather prediction, 57 00:03:46.650 --> 00:03:50.680 and climate research. Erich Stocker: As we improve the precipitation 58 00:03:50.700 --> 00:03:54.690 retrievals that form the basis for these merged products 59 00:03:54.710 --> 00:03:58.710 that will get better and better, and we'll be seeing actual satellite data 60 00:03:58.730 --> 00:04:02.760 rather than just forecasts. [raindrops falling] 61 00:04:02.780 --> 00:04:06.790 62 00:04:06.810 --> 00:04:10.820 63 00:04:10.840 --> 00:04:14.840 64 00:04:14.860 --> 00:04:17.838